A case for location based contact tracing.
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ABSTRACT:
SUBMITTER: Pokharel A
PROVIDER: S-EPMC8206884 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Contact tracing is currently one of the most effective measures to contain the COVID-19 pandemic. In order to identify persons that would otherwise not be known or remembered and to keep the time delay when reporting an infection and when contacting people as short as possible, digital contact tracing using smartphones seems to be a reasonable measure additional to manual contact tracing. Although first modelling studies predicted a positive effect in terms of prompt contact tracing, no empirically reliable data are as yet available, neither on the population-wide benefit nor on the potential risks of contact tracing apps. Risk-benefit assessment of such an app includes investigating whether such an app fulfils its purpose, as also research on the effectiveness, risks and side effects, and implementation processes (e.?g. planning and inclusion of different participants). The aim of this article was to give an overview of possible public health benefits as well as technical, social, legal and ethical aspects of a contact-tracing app in the context of the COVID-19 pandemic. Furthermore, conditions for the widest possible use of the app are presented.
| S-EPMC7536383 | biostudies-literature
Project description:ImportanceContact tracing is a multistep process to limit SARS-CoV-2 transmission. Gaps in the process result in missed opportunities to prevent COVID-19.ObjectiveTo quantify proportions of cases and their contacts reached by public health authorities and the amount of time needed to reach them and to compare the risk of a positive COVID-19 test result between contacts and the general public during 4-week assessment periods.Design, setting, and participantsThis cross-sectional study took place at 13 health departments and 1 Indian Health Service Unit in 11 states and 1 tribal nation. Participants included all individuals with laboratory-confirmed COVID-19 and their named contacts. Local COVID-19 surveillance data were used to determine the numbers of persons reported to have laboratory-confirmed COVID-19 who were interviewed and named contacts between June and October 2020.Main outcomes and measuresFor contacts, the numbers who were identified, notified of their exposure, and agreed to monitoring were calculated. The median time from index case specimen collection to contact notification was calculated, as were numbers of named contacts subsequently notified of their exposure and monitored. The prevalence of a positive SARS-CoV-2 test among named and tested contacts was compared with that jurisdiction's general population during the same 4 weeks.ResultsThe total number of cases reported was 74 185. Of these, 43 931 (59%) were interviewed, and 24 705 (33%) named any contacts. Among the 74 839 named contacts, 53 314 (71%) were notified of their exposure, and 34 345 (46%) agreed to monitoring. A mean of 0.7 contacts were reached by telephone by public health authorities, and only 0.5 contacts per case were monitored. In general, health departments reporting large case counts during the assessment (≥5000) conducted smaller proportions of case interviews and contact notifications. In 9 locations, the median time from specimen collection to contact notification was 6 days or less. In 6 of 8 locations with population comparison data, positive test prevalence was higher among named contacts than the general population.Conclusions and relevanceIn this cross-sectional study of US local COVID-19 surveillance data, testing named contacts was a high-yield activity for case finding. However, this assessment suggests that contact tracing had suboptimal impact on SARS-CoV-2 transmission, largely because 2 of 3 cases were either not reached for interview or named no contacts when interviewed. These findings are relevant to decisions regarding the allocation of public health resources among the various prevention strategies and for the prioritization of case investigations and contact tracing efforts.
| S-EPMC8176334 | biostudies-literature
Project description:People continue to use technology in new ways, and how governments harness digital information should consider privacy and security concerns. During COVID19, numerous countries deployed digital contact tracing that collect location data from user's smartphones. However, these apps had low adoption rates and faced opposition. We launched an interdisciplinary study to evaluate smartphone location data concerns among college students in the US. Using interviews and a large survey, we find that college students have higher concerns regarding privacy, and place greater trust in local government with their location data. We discuss policy recommendations for implementing improved contact tracing efforts.
| S-EPMC10664924 | biostudies-literature
Project description:BackgroundThe air borne SARS-CoV-2 poses a high threat to the elderly and people with underlying diseases. COVID-19 spread quickly in South German nursing homes and for this reason called for preventive measures by the German government. The aim of this paper is to showcase the testing strategies implemented by the Public Health Department Reutlingen to control the spread of COVID-19 in local nursing homes and to report the results thereof.MethodsThis study reports COVID-19 outbreaks in nursing homes in Reutlingen County and how they were dealt with through extensive testing, contact tracing, isolation and hygiene inspections. The testing strategy consisted of three phases: In phase 1 only suspected cases, in phase 2 all staff and residents, and in phase 3 all suspected cases and their contacts were tested.ResultsNearly all residents (98%) and staff members (92%) of all nursing homes in Reutlingen County were tested for SARS-COV-2. 25 of 37 nursing homes had COVID-19 cases, 5 had 30-81 cases/home. 62% of the 395 nursing homes cases were residents, but less than half of them exhibited symptoms (41%). The cases uncovered in nursing homes represented 26% of all 1529 cases in Reutlingen County during the time of this study.ConclusionsMany COVID-19 cases were discovered through extensive testing, allowing for early interventions. The results shed light on the COVID-19 situation in nursing homes and allowed for individually designed preventive measures. The results also lead to a change in the German legislation. The outbreak management methods of the Public Health Department Reutlingen may also be applicable in other countries.
| S-EPMC8961262 | biostudies-literature
Project description:BackgroundLow engagement in contact tracing for COVID-19 dramatically reduces its impact, but little is known about how experiences, environments and characteristics of cases and contacts influence engagement.MethodsWe recruited a convenience sample of COVID-19 cases and contacts from the New Haven Health Department's contact tracing program for interviews about their contact tracing experiences. We analyzed transcripts thematically, organized themes using the Capability, Opportunity, Motivation, Behavior (COM-B) model, and identified candidate interventions using the linked Behavior Change Wheel Framework.ResultsWe interviewed 21 cases and 12 contacts. Many felt physically or psychologically incapable of contact tracing participation due to symptoms or uncertainty about protocols. Environmental factors and social contacts also influenced engagement. Finally, physical symptoms, emotions and low trust in and expectations of public health authorities influenced motivation to participate.ConclusionTo improve contact tracing uptake, programs should respond to clients' physical and emotional needs; increase clarity of public communications; address structural and social factors that shape behaviors and opportunities; and establish and maintain trust. We identify multiple potential interventions that may help achieve these goals.
| S-EPMC9595089 | biostudies-literature
Project description:A plethora of measures are being combined in the attempt to reduce SARS-CoV-2 spread. Due to its sustainability, contact tracing is one of the most frequently applied interventions worldwide, albeit with mixed results. We evaluate the performance of digital contact tracing for different infection detection rates and response time delays. We also introduce and analyze a novel strategy we call contact prevention, which emits high exposure warnings to smartphone users according to Bluetooth-based contact counting. We model the effect of both strategies on transmission dynamics in SERIA, an agent-based simulation platform that implements population-dependent statistical distributions. Results show that contact prevention remains effective in scenarios with high diagnostic/response time delays and low infection detection rates, which greatly impair the effect of traditional contact tracing strategies. Contact prevention could play a significant role in pandemic mitigation, especially in developing countries where diagnostic and tracing capabilities are inadequate. Contact prevention could thus sustainably reduce the propagation of respiratory viruses while relying on available technology, respecting data privacy, and most importantly, promoting community-based awareness and social responsibility. Depending on infection detection and app adoption rates, applying a combination of digital contact tracing and contact prevention could reduce pandemic-related mortality by 20-56%.
| S-EPMC8277769 | biostudies-literature
Project description:Traditional contact tracing relies on knowledge of the interpersonal network of physical interactions, where contagious outbreaks propagate. However, due to privacy constraints and noisy data assimilation, this network is generally difficult to reconstruct accurately. Communication traces obtained by mobile phones are known to be good proxies for the physical interaction network, and they may provide a valuable tool for contact tracing. Motivated by this assumption, we propose a model for contact tracing, where an infection is spreading in the physical interpersonal network, which can never be fully recovered; and contact tracing is occurring in a communication network which acts as a proxy for the first. We apply this dual model to a dataset covering 72 students over a 9 month period, for which both the physical interactions as well as the mobile communication traces are known. Our results suggest that a wide range of contact tracing strategies may significantly reduce the final size of the epidemic, by mainly affecting its peak of incidence. However, we find that for low overlap between the face-to-face and communication interaction network, contact tracing is only efficient at the beginning of the outbreak, due to rapidly increasing costs as the epidemic evolves. Overall, contact tracing via mobile phone communication traces may be a viable option to arrest contagious outbreaks.
| S-EPMC4006791 | biostudies-other
Project description:Goal: The COVID-19 pandemic has emerged as the most severe public health crisis in over a century. As of January 2021, there are more than 100 million cases and 2.1 million deaths. For informed decision making, reliable statistical data and capable simulation tools are needed. Our goal is to develop an epidemic simulator that can model the effects of random population testing and contact tracing. Methods: Our simulator models individuals as particles with the position, velocity, and epidemic status states on a 2D map and runs an SEIR epidemic model with contact tracing and testing modules. The simulator is available on GitHub under the MIT license. Results: The results show that the synergistic use of contact tracing and massive testing is effective in suppressing the epidemic (the number of deaths was reduced by 72%). Conclusions: The Particle-based COVID-19 simulator enables the modeling of intervention measures, random testing, and contact tracing, for epidemic mitigation and suppression.
| S-EPMC8545033 | biostudies-literature
Project description:BackgroundAs of 24th of August 2020, the number of global COVID-19 confirmed cases is nearly 24 million. In the same period, the number of recorded infections in Thailand has remained at approximately 3300. This paper explores the specifics of COVID-19 or SARS-CoV-2 transmissions in Phuket, Thailand's second most visited tourist destination.MethodsHigh-risk contacts recorded by Phuket Provincial Public Health Office were analysed using the Probit model to investigate the risk factors for transmission from confirmed COVID-19 cases to their high-risk contacts. The analysis was further focused on the impact of quarantine measures in state provided facilities on contacts' probability of infection.Findings15.6% of 1108 high-risk contacts were found to be infected, and they accounted for 80% of 214 confirmed cases in Phuket till 29th April 2020. Moreover, 10.68% of all high-risk contacts were confirmed to be infected before the quarantine, and 4.55% after the policy was enforced. In addition, a contact who lived within the same household with a confirmed case was 25% more exposed to infection when compared to a contact who did not share a household.InterpretationResults confirmed that the quarantine policy, which mandated individual isolation in the state provided facilities for all high-risk contacts, diminished contact's chance of infection from the confirmed cases, especially in the epicenter districts. Our findings confirmed that sharing accommodation with an infected case, and exposure to a case with several documented secondary transmission, generally increased the SARS-CoV-2 infection probability. Finally, some confirmed cases do exhibit a higher risk of spreading SARS-CoV-2 to their contacts compared to a typical confirmed case. Further studies of high reproduction groups of infected patients are recommended.FundingNo funding was received for this research.
| S-EPMC7503192 | biostudies-literature
Project description:Abstract There are several Contact Tracing solutions since the outbreak of SARS COVID-19. All these solutions are localized—specific to a country. The Apps supported by these solutions do not interwork with each other. There are no standards to the proximity data collected by these Apps. Once the international travel restrictions are relaxed, this will become an issue. This paper explores this issue, by addressing one of the key requirements of Contact Tracing solutions. All the current solutions use an Identifier, Proximity Identifier (PID), that anonymously represents the user in the proximity data exchanged. The PID used in these applications varies in their structure, management and properties. This paper first identifies the common desirable properties of PID, including some non-obvious ones for its global application. This identification is essential for the design and development of the Contact Tracing solution that can work across boundaries seamlessly. The paper also evaluates representative solutions from two different design classes against these properties.
| S-EPMC8344825 | biostudies-literature